Unité mixte de recherche 7235

Minimum Variance Portfolio Optimisation under Parameter Uncertainty: A Robust Control Approach

Bertrand Maillet, Sessi Tokpavi, Benoit Vaucher

[en]The global minimum variance portfolio computed using the sample covariance matrix is known to be negatively affected by parameter uncertainty. Using a robust control approach, we introduce a portfolio rule for investors who wish to invest in the global minimum variance portfolio due to its strong historical track record but seek a rule that is robust to parameter uncertainty. Our robust portfolio theoretically corresponds to the global minimum variance portfolio in the worst-case scenario, with respect to a set of plausible alternative estimators of the covariance matrix, in the neighbourhood of the sample covariance matrix. Hence, it provides protection against errors in the reference sample covariance matrix. Monte Carlo simulations illustrate the dominance of the robust portfolio over its non-robust counterpart, in terms of portfolio stability, variance and risk-adjusted returns. Empirically, we compare the out-of-sample performance of the robust portfolio to various competing minimum variance portfolio rules in the literature. We observe that the robust portfolio often has lower turnover and variance and higher Sharpe ratios than the competing minimum variance portfolios.[/en]

AGENDA

mardi 5 décembre 2023

Recherche et Economie et Socioéconomie Politique, des Institutions et des Régulations (RESPIR)

Clément Fontan (UC Louvain)

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jeudi 7 décembre 2023

Groupe de travail Economie Comportementale

Vincent Lenglin (Université Catholique de Lille)

TBA

jeudi 7 décembre 2023

Doctorants

Emmanuelle Faure

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Law, Institutions and Economics in Nanterre (LIEN)

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Économies du monde musulman

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Dette en Egypte : conjoncture défavorable ou structure vulnérable ?

jeudi 14 décembre 2023

Lunch

Hugo ORIOLA

Salle 101-102 à 12h

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jeudi 14 décembre 2023

Développement Durable Environnement et Energie (DDEE)

Emeline Bezin (CNRS/CREM)

Salle 101-102

TBA

jeudi 14 décembre 2023

Séminaire Econom’IA

Benjamin Ooghe-Tabanou (médialab - Sciences Po Paris)

Salle G614A de 11h à 12h30

Outils, méthodes et productions numériques à partir de données du web au médialab de Sciences Po

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